The influence of anthropomorphic appearance of artificial intelligence products on consumer behavior and brand evaluation under different product types

While artificial intelligence products are widely used in the market, their anthropomorphic appearance design is becoming a frontier issue in product strategy and consumer behavior research. The aim of this study was to investigate the influence of anthropomorphic appearance on consumer behavior and brand evaluation under different AI product types. It was conducted in China, a new but rapidly-growing country in the field of Internet, AI technology and AI product consumption. This study conducted four situational experiments with a 2 (anthropomorphic design: anthropomorphic vs. non-anthropomorphic) × 2 (product type: hedonic vs. utilitarian) between subjects’ experimental design. Data was collected from 1172 Chinese “Digital Natives” by using a structured questionnaire. The findings revealed that for hedonic AI products, anthropomorphic appearance improves consumers' purchase intention and brand evaluation through perceived entertainment, and intelligence level significantly moderates the mediating effect of perceived entertainment; while for practical AI products, anthropomorphic appearance improves consumers' purchase intention and brand evaluation through perceived usefulness, and intelligence level does not significantly moderate the mediating effect of perceived usefulness. There is no significant moderating effect of intelligence level on perceived usefulness. The study contributes to development and validation of a more comprehensive understanding and theoretical foundation of anthropomorphism, and furthermore explores the impact of anthropomorphic appearance on consumer behavior and brand evaluation under different AI product types. This study also provides insights for companies to apply anthropomorphic strategies.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

知识型员工冗余对中小上市公司二元创新的影响：环境特征的调节作用

以277家中小板和创业板上市公司2012-2017年平衡面板数据为样本，利用泊松模型，实证分析知识型员工冗余与企业二元创新的关系，并探讨外部环境特征（要素市场发育程度和市场不确定性）的调节机理。研究表明：企业应保持一定的知识型员工冗余，促进企业二元式创新，过多或过少的知识型员工冗余均不利于企业开展创新活动；不同的环境特征对二者间关系的调节作用存在异质性，要素市场发育程度会减弱知识型员工冗余与探索式创新、利用式创新间关系，而市场不确定性会加强知识型员工冗余与探索式创新、利用式创新间关系。     

我国“一带一路”沿线地区风险投资时空分布及影响因素研究

深入分析我国“一带一路”沿线地区风险投资时空格局及影响因素，有助于促进创新创业与企业发展、提高区域科技创新水平。运用空间分析方法和空间计量模型，对2003-2018年我国“一带一路”沿线139个城市风险投资的时空分布特征及影响因素进行分析，结果表明：①沿线地区的风险投资发展具有不均衡性，呈现为沿海高、西部低的分异格局；②风险投资的全局自相关系数均为正，呈现出明显的空间集聚特征；③风险投资机构数、国家高新区数量、风险投资退出、政府引导基金发展、财政科技支出对区域风险投资具有显著促进作用，环境污染对风险投资有一定抑制作用。随着ESG投资理念逐渐获得认可，沿线地区可以通过提升绿色发展水平促进风险投资发展。     

长江经济带人才集聚水平测度及时空演变研究——基于价值链视角

基于价值链视角，构建涵盖人才资源在区域空间层面集聚生成、地区配置、效能产出3个维度在内的区域人才集聚水平评价指标体系，采用专家咨询AHP-信息熵组合赋权法构建综合评价模型和耦合协调度模型，对2010—2018年长江经济带沿线省市人才集聚水平进行测度与时空演化特征分析。结果表明，就长江经济带整体而言，考察期内地区人才集聚水平总体呈现逐年上升态势，但仍处于低水平状态；沿线省市人才集聚水平差异显著，缩小趋势渐缓，整体呈现局部高水平、全局低效率的不利境况；各省市人才集聚水平关键维度的耦合协调度整体呈显著波动递增态势，但内部耦合协调度存在不平衡发展问题，影响地区人才集聚水平整体提升。为提升长江经济带人才集聚水平，推进沿线地区协调发展，需强化区域人才合作机制，采取差别化精准策略破解沿线地区人才集聚低水平、不协调的短板因素。     

The impact of research collaboration on academic performance: An empirical analysis for some European countries

The aim of this paper is to investigate the impact of internal and external research collaborations on the scientific performance of academic institutions. The data are derived from the international SCOPUS database. We consider both quantity (the number of publications) and quality indicators (the field-weighted citation impact and the share of publications in the 10% most-cited articles) to evaluate universities' performance in some European countries (Germany, France, Italy, the UK and Russia). To this end, we develop a non-overlapping generations model to evidence the theoretical idea of research externalities between academic institutions. Moreover, we implement an empirical model to determine the extent to which the impact of internal and external collaborations on universities' performance is sensitive to the geographical dimension of the data.     

Performance evaluation of China's high-tech innovation process: Analysis based on the innovation value chain

The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.     

Overconfidence and tax avoidance: The role of CEO and CFO interaction

We investigate how overconfident CEOs and CFOs may interact to influence firms’ tax avoidance. We adopt an equity measure to capture overconfident CEOs and CFOs and utilize multiple measures to identify companies’ tax-avoidance activities. We document that CFOs, as CEOs’ business partners, play an important role in facilitating and executing overconfident CEOs’ decisions in regard to tax avoidance. Specifically, we find that companies are more likely to engage in tax-avoidance activities when they have both overconfident CEOs and overconfident CFOs, compared with companies that have other combinations of CEO/CFO overconfidence (e.g., an overconfident CEO with a non-overconfident CFO), which is consistent with the False Consensus Effect Theory. Our study helps investors, regulators, and policymakers understand companies’ decision-making processes with regard to tax avoidance.     

Understanding precedents for frontline employee turnover in luxury hotels: Emotional intelligence as a unifying factor

Current turnover research fails to serve the needs of an industry that is long plagued by employee turnover. Existing literature focuses more on evaluating bundles of human resource practices and fail to provide precise and clear guidance for practitioners. This study proposes that emotional intelligence (EI) unifies sufficient individual factors and organizational factors that affect employee turnover and serves as a single significant precedent for turnover. Data were collected from frontline employees at eight luxury hotels. The direct, indirect, and total impacts of employee EI on employee turnover were tested by structural equation modeling and bootstrap tests. The results suggest that EI has significant indirect impacts through the mediation of perceived organizational support, pay satisfaction and job burnout, and significant total impacts on turnover. Implication suggestions include integrating EI into the recruiting process for new employees and providing training opportunities for current employees to improve their EI.     

Characteristics and implications of Chinese macroeconomic data revisions

The research examining macroeconomic data for developed economies suggests that an understanding of the nature of data revisions is important both for the production of accurate macroeconomic forecasts and for forecast evaluation. This paper focuses on Chinese data, for which there has been substantial debate about data quality for some time. The key finding in this paper is that, while it is true that the Chinese macroeconomic data revisions are not well-behaved, they are not very different from similarly-timed U.S. macroeconomic data revisions. The positive bias in Chinese real GDP revisions is a result of the fast-growing service sector, which is notably hard to measure in real time. A better understanding of the revisions process is particularly helpful for studies of the forecast errors from surveys of forecasters, where the choice of the vintage for outcomes may have an impact on the estimated forecast errors.